DP-100 Online Practice Questions and Answers

You create an experiment in Azure Machine Learning Studio. You add a training dataset that contains 10,000 rows. The first 9,000 rows represent class 0 (90 percent).

The remaining 1,000 rows represent class 1 (10 percent).

The training set is imbalances between two classes. You must increase the number of training examples for class 1 to 4,000 by using 5 data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment.

You need to configure the module.

Which values should you use? To answer, select the appropriate options in the dialog box in the answer area.

NOTE: Each correct selection is worth one point.

Hot Area:

HOTSPOT

The finance team asks you to train a model using data in an Azure Storage blob container named finance-data.

You need to register the container as a datastore in an Azure Machine Learning workspace and ensure that an error will be raised if the container does not exist.

How should you complete the code? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Hot Area:

HOTSPOT

You have an Azure Machine Learning workspace

You plan to use the Azure Machine Learning SDK for Python v1 to submit a job to run a training script.

You need to complete the script to ensure that it will execute the training script.

How should you complete the script? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point

Hot Area:

DRAG DROP

You need to produce a visualization for the diagnostic test evaluation according to the data visualization requirements.

Which three modules should you recommend be used in sequence? To answer, move the appropriate modules from the list of modules to the answer area and arrange them in the correct order.

Select and Place:

Your team is building a data engineering and data science development environment. The environment must support the following requirements:

1.

support Python and Scala

2.

compose data storage, movement, and processing services into automated data pipelines

3.

the same tool should be used for the orchestration of both data engineering and data science

4.

support workload isolation and interactive workloads

5.

enable scaling across a cluster of machines

You need to create the environment.

What should you do?

A. Build the environment in Apache Hive for HDInsight and use Azure Data Factory for orchestration.

B. Build the environment in Azure Databricks and use Azure Data Factory for orchestration.

C. Build the environment in Apache Spark for HDInsight and use Azure Container Instances for orchestration.

D. Build the environment in Azure Databricks and use Azure Container Instances for orchestration.

You plan to run a script as an experiment using a Script Run Configuration. The script uses modules from the scipy library as well as several Python packages that are not typically installed in a default conda environment.

You plan to run the experiment on your local workstation for small datasets and scale out the experiment by running it on more powerful remote compute clusters for larger datasets.

You need to ensure that the experiment runs successfully on local and remote compute with the least administrative effort.

What should you do?

A. Do not specify an environment in the run configuration for the experiment. Run the experiment by using the default environment.

B. Create a virtual machine (VM) with the required Python configuration and attach the VM as a compute target. Use this compute target for all experiment runs.

C. Create and register an Environment that includes the required packages. Use this Environment for all experiment runs.

D. Create a config.yaml file defining the conda packages that are required and save the file in the experiment folder.

E. Always run the experiment with an Estimator by using the default packages.

You use the Two-Class Neural Network module in Azure Machine Learning Studio to build a binary classification model. You use the Tune Model Hyperparameters module to tune accuracy for the model.

You need to configure the Tune Model Hyperparameters module.

Which two values should you use? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A. Number of hidden nodes

B. Learning Rate

C. The type of the normalizer

D. Number of learning iterations

E. Hidden layer specification

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while

others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You create a model to forecast weather conditions based on historical data.

You need to create a pipeline that runs a processing script to load data from a datastore and pass the processed data to a machine learning model training script.

Solution: Run the following code:

Does the solution meet the goal?

A. Yes

B. No

You run an experiment that uses an AutoMLConfig class to define an automated machine learning task with a maximum of ten model training iterations. The task will attempt to find the best performing model based on a metric named accuracy.

You submit the experiment with the following code:

You need to create Python code that returns the best model that is generated by the automated machine learning task. Which code segment should you use?

A. best_model = automl_run.get_details()

B. best_model = automl_run.get_metrics()

C. best_model = automl_run.get_file_names()[1]

D. best_model = automl_run.get_output()[1]

You create a multi-class image classification deep learning model that uses the PyTorch deep learning framework.

You must configure Azure Machine Learning Hyperdrive to optimize the hyperparameters for the classification model.

You need to define a primary metric to determine the hyperparameter values that result in the model with the best accuracy score.

Which three actions must you perform? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

A. Set the primary_metric_goal of the estimator used to run the bird_classifier_train.py script to maximize.

B. Add code to the bird_classifier_train.py script to calculate the validation loss of the model and log it as a float value with the key loss.

C. Set the primary_metric_goal of the estimator used to run the bird_classifier_train.py script to minimize.

D. Set the primary_metric_name of the estimator used to run the bird_classifier_train.py script to accuracy.

E. Set the primary_metric_name of the estimator used to run the bird_classifier_train.py script to loss.

F. Add code to the bird_classifier_train.py script to calculate the validation accuracy of the model and log it as a float value with the key accuracy.

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You train a classification model by using a logistic regression algorithm.

You must be able to explain the model's predictions by calculating the importance of each feature, both as an overall global relative importance value and as a measure of local importance for a specific set of predictions.

You need to create an explainer that you can use to retrieve the required global and local feature importance values.

Solution: Create a MimicExplainer.

Does the solution meet the goal?

A. Yes

B. No

You are planning to register a trained model in an Azure Machine Learning workspace.

You must store additional metadata about the model in a key-value format. You must be able to add new metadata and modify or delete metadata after creation.

You need to register the model.

Which parameter should you use?

A. description

B. model_framework

C. tags

D. properties

You are evaluating a completed binary classification machine learning model.

You need to use the precision as the valuation metric.

Which visualization should you use?

A. Binary classification confusion matrix

B. box plot

C. Gradient descent

D. coefficient of determination

You create a workspace by using Azure Machine Learning Studio.

You must run a Python SDK v2 notebook in the workspace by using Azure Machine Learning Studio. You must preserve the current values of variables set in the notebook for the current instance.

You need to maintain the state of the notebook.

What should you do?

A. Change the compute.

B. Change the current kernel

C. Stop the compute.

D. Stop the current kernel.

You train and register an Azure Machine Learning model.

You plan to deploy the model to an online endpoint.

You need to ensure that applications will be able to use the authentication method with a non-expiring artifact to access the model.

Solution: Create a managed online endpoint and set the value of its auth_mode parameter to key. Deploy the model to the online endpoint.

Does the solution meet the goal?

A. Yes

B. No